Abstract
Traditional suspension system has fixed damping properties and provides constant response to varying road types. On the contrary, active suspension uses a linear motor which can adjust its damping properties in real time to provide enhanced passenger comfort experience. In this study the transient response of two control strategies Linear Quadratic Regulator (LQR) and Model Predictive Control (MPC) have been compared for an active suspension system. A force optimization in active suspension has been illustrated by comparing the LQR and the MPC control schemes. Quadratic cost function for both the control schemes has been optimized for the state and input variables. Simulation is carried out using MATLAB-SIMULINK and effect of the variation of the weights has been studied. The reduction in actuator force usage when MPC is used has been reported.
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Narayan, J., Gorji, S.A., Ektesabi, M.M. (2021). Force Optimization for an Active Suspension System in a Quarter Car Model Using MPC. In: Rao, Y.V.D., Amarnath, C., Regalla, S.P., Javed, A., Singh, K.K. (eds) Advances in Industrial Machines and Mechanisms. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-1769-0_42
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DOI: https://doi.org/10.1007/978-981-16-1769-0_42
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